We need to go deeper. Thought experiment to follow:
Consider the question: "Does technical analysis work, and if so, why?"
To answer this question, we invent a zero-sum n-player game, which we shall call "Bitcoin".
Working from the very simple rules of the game, we can rediscover some pretty cool findings from economics and game-theory.
Note: This is a quick hack first draft. Just laying some groundwork.
The Rules Of The Game are as follows:
• Players compete for points.
• Points have some utility, external to the game.
• Points can be generated at some cost, external to the game.
• Prize pool increases from 0 to 21 million points over the duration of the game.
• Number of points generated per round is cut in half after some constant number of rounds.
• Players are initially uncoordinated.
• Players are allowed to communicate, but compete for points.
• Players tend to seek to maximize their current balance.
• Game state includes points, time, price, volume,.
• Initial conditions are 0, 0, 0, 0, respectively.
Players can perform any one of three actions per round:
• (Buy, Volume).
• (Sell, Volume).
• Abstain.
• Buying comes at some cost, external to the game.
• Selling gives some profit, external to the game.
• Players can make one move per turn.
• Most players will choose to abstain in any given round.
• Some players will make a move, on occasion.
Explaining non-random patterns emerging from the initially random* moves of uncoordinated agents:
• Successful (lucky?) players will try to repeat successful (lucky?) behaviour.
• Successful players have some history of making successful moves.
• Successful players tend to repeat successful moves when similar conditions reappear.
• Successful players tend to communicate their "history".
• Unlucky players tend to shut up, but will try to emulate successful (lucky?) players.
This is sufficient to explain coordination without communication,
as well as how coordination can be augmented by communication.
From whence Technical Analysis?
• When faced with making a decision, players tend to search the game history for similar states, outcomes.
• Given enough data, players will try to find some ([best match],next best-action) rule.
• Human players (involuntarily, unconsciously) invent rules for making predictions.
• Non-human players will be programmed with the formalized but otherwise similar rules to those of human players.
• Players will tend to independently discover the same/similar ([best match],next best-action) in initially random data.
• This causes such patterns to repeat, but only imperfectly. Players try to outwit other players. The game iterates.
• This leads to repeating of historical patterns. Trends emerge.
• Following trends can lead to higher expected score than random actions, or countertrend actions.**
• Technical analysis (various methods to find a next best-action) can be used to coordinate/collaboration of players in the game,
creating/finding Schelling points without need for mutual communication.
*Doubtful, bias likely. (Needs explaining.)
**This statement needs backing, empirical or otherwise.
Wouldn't it be cool to run this as a simulation, with a computer program to implement the game rules, and using humans as players?
PS: Rediscovering the process that leads to the discovery/creation of hidden Schelling Points feels pretty awesome.